SoroushVahidi/scidocs huggingface dataset:
Abstract Cryptography
(2011)

Cryptography Ueli Maurer ETH Zurich FOSAD 2009, Bertinoro, Aug./Sept. 2009. Abstract CryptographyCryptography Ueli Maurer ETH Zurich FOSAD 2009, Bertinoro, Aug./Sept. 2009. “I can only understand simple things.” JAMES MASSEY Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitabilityion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understandingion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Abstraction Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Goals of this talk: • Introduce layers of abstraction in cryptography. • Ex mples of abstract definitions and proofs. • Announce new security framework “abstract cryptography” (with Renato Renner).ion Abstraction: eliminate irrelevant details from consideration Examples: group, field, vector space, relation, graph, .... Goals of abstraction: • simpler definitions • generality of results • simpler proofs • elegance • didactic suitability • understanding Goals of this talk: • Introduce layers of abstraction in cryptography. • Ex mples of abstract definitions and proofs. • Announce new security framework “abstract cryptography” (with Renato Renner). Motivating example: One-time pad 1 C , C , ... 1 ciphertext 1 2 key 2 1 key 2 1 2 2 addition modulo 2 M , M , ... M , M , ... plaintext plaintext K , K , ... K , K , ... Motivating example: One-time pad 1 C , C , ... 1 ciphertext 1 2 key 2 1 key 2 1 2 2 addition modulo 2 M , M , ... M , M , ... plaintext plaintext K , K , ... K , K , ... Perfect secrecy (Shannon): C and M statist. independent. One-time pad in terms of systems .
A low cost ultra-wideband pulse transceiver
(2010)

A low cost pulse transceiver has been developed for measuring the electrical properties of materials. The transceiver generates an ultra wide band (UWB) pulse as well as samples the received pulse. The pulse generator has been designed using a silicon-germanium (SiGe) analog comparator which is a possible alternative to step recovery diodes. The pulse is received by an extended time sampling circuit. The sampling circuit presented is an alternative design that does not require the use of a broadband balun.
A Survey of Shortest-Path Algorithms
(2017)

A shortest-path algorithm finds a path containing the minimal cost between two vertices in a graph. A plethora of shortest-path algorithms is studied in the literature that span across multiple disciplines. This paper presents a survey of shortest-path algorithms based on a taxonomy that is introduced in the paper. One dimension of this taxonomy is the various flavors of the shortest-path problem. There is no one general algorithm that is capable of solving all variants of the shortest-path problem due to the space and time complexities associated with each algorithm. Other important dimensions of the taxonomy include whether the shortest-path algorithm operates over a static or a dynamic graph, whether the shortest-path algorithm produces exact or approximate answers, and whether the objective of the shortest-path algorithm is to achieve time-dependence or is to only be goal directed. This survey studies and classifies shortest-path algorithms according to the proposed taxonomy. The survey also presents the challenges and proposed solutions associated with each category in the taxonomy.
Image super-resolution by estimating the enhancement weight of self example and external missing patches
(2017)

Image super-resolution (SR) is the process of generating a high-resolution (HR) image using one or more low-resolution (LR) inputs. Many SR methods have been proposed, but generating the small-scale structure of an SR image remains a challenging task. We hence propose a single-image SR algorithm that combines the benefits of both internal and external SR methods. First, we estimate the enhancement weights of each LR-HR image patch pair. Next, we multiply each patch by the estimated enhancement weight to generate an initial SR patch. We then employ a method to recover the missing information from the high-resolution patches and create that missing information to generate a final SR image. We then employ iterative back-projection to further enhance visual quality. The method is compared qualitatively and quantitatively with several state-of-the-art methods, and the experimental results indicate that the proposed framework provides high contrast and better visual quality, particularly for non-smooth texture areas.
Tailoring graph-coloring register allocation for runtime compilation
(2006)

Just-in-time compilers are invoked during application execution and therefore need to ensure fast compilation times. Consequently, runtime compiler designers are averse to implementing compile-time intensive optimization algorithms. Instead, they tend to select faster but less effective transformations. In this paper, we explore this trade-off for an important optimization - global register allocation. We present a graph-coloring register allocator that has been redesigned for runtime compilation. Compared to Chaitin- Briggs [7], a standard graph-coloring technique, the reformulated algorithm requires considerably less allocation time and produces allocations that are only marginally worse than those of Chaitin-Briggs. Our experimental results indicate that the allocator performs better than the linear-scan and Chaitin-Briggs allocators on most benchmarks in a runtime compilation environment. By increasing allocation efficiency and preserving optimization quality, the presented algorithm increases the suitability and profitability of a graph-coloring register allocation strategy for a runtime compiler.
Introduction to Information Retrieval Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schtze (Stanford University, Yahoo! Research, and University of Stuttgart) Cambridge: Cambridge University Press, 2008, xxi+482 pp; hardbound, ISBN 978-0-521-86571-5, $60.00
(2009)

Introduction to Information Retrieval is the first textbook with a coherent treatment of classical and web information retrieval, including web search and the related areas of text classification and text clustering. Written from a computer science perspective, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents and of methods for evaluating systems, along with an introduction to the use of machine learning methods on text collections. Designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also interest researchers and professionals. A complete set of lecture slides and exercises that accompany the book are available on the web.
EMI filter design and optimization for both AC and DC side in a DC-fed motor drive system
(2013)

This paper proposes an EMI filter design and optimization method for both AC and DC side in a DC-fed motor drive system. Based on the noise generation and propagation mechanism, the analysis of common mode (CM) and differential mode (DM) EMI noise equivalent circuits is provided. Based on those equivalent circuits, this paper investigates the system EMI noise between AC and DC side, which shows the interaction between DM and CM noises and the interaction between adding AC and DC side filters. With these considerations, an optimized EMI filter design procedure is proposed to design CM and DM filters for both AC and DC sides. To minimize the impact on the EMI noise of one side caused by adding filter on the other side, certain order must be followed to design AC and DC CM and DM filters. Moreover, the EMI filter weight optimization method is also discussed to get the minimum weight of EMI filter and improve system power density. Simulation and experimental results verify the interaction between AC and DC filters and show that EMI filters can be designed to suppress both AC and DC EMI noise to meet the standard with the proposed EMI filter design method.
A Survey on Potential Applications of Honeypot Technology in Intrusion Detection Systems
(2015)

Information security in the sense of personal and institutional has become a top priority in digitalized modern world in parallel to the new technological developments. Many methods, tools and technologies are used to provide the information security of IT systems. These are considered, encryption, authentication, firewall, and intrusion detection and prevention systems. Moreover, honeypot systems are proposed as complementary structures. This paper presents the overall view of the publications in IDS, IPS and honeypot systems. Recently, honeypot systems are anymore used in connection with intrusion detection systems. So this paper describes possible implementation of honeypot technologies combined with IDS/IPS in a network. Studies in the literature have shown intrusion detection systems cannot find the 0-day vulnerabilities. The system provided by the honeypots and intrusion detection systems in the network, might detect new exploit and hacker attempt. Index Terms – Information security, Intrusion detection system (IDS), Intrusion prevention system (IPS), Honeypot, Network Security.
Does core strength training influence running kinetics, lower-extremity stability, and 5000-M performance in runners?
(2009)

Although strong core muscles are believed to help athletic performance, few scientific studies have been conducted to identify the effectiveness of core strength training (CST) on improving athletic performance. The aim of this study was to determine the effects of 6 weeks of CST on ground reaction forces (GRFs), stability of the lower extremity, and overall running performance in recreational and competitive runners. After a screening process, 28 healthy adults (age, 36.9 +/- 9.4 years; height, 168.4 +/- 9.6 cm; mass, 70.1 +/- 15.3 kg) volunteered and were divided randomly into 2 groups (n = 14 in each group). A test-retest design was used to assess the differences between CST (experimental) and no CST (control) on GRF measures, lower-extremity stability scores, and running performance. The GRF variables were determined by calculating peak impact, active vertical GRFs (vGRFs), and duration of the 2 horizontal GRFs (hGRFs), as measured while running across a force plate. Lower-extremity stability was assessed using the Star Excursion Balance Test. Running performance was determined by 5000-m run time measured on outdoor tracks. Six 2 (pre, post) x 2 (CST, control) mixed-design analyses of variance were used to determine the influence of CST on each dependent variable, p < 0.05. Twenty subjects completed the study (nexp = 12 and ncon = 8). A significant interaction occurred, with the CST group showing faster times in the 5000-m run after 6 weeks. However, CST did not significantly influence GRF variables and lower-leg stability. Core strength training may be an effective training method for improving performance in runners.
A performance and energy comparison of FPGAs, GPUs, and multicores for sliding-window applications
(2012)

With the emergence of accelerator devices such as multicores, graphics-processing units (GPUs), and field-programmable gate arrays (FPGAs), application designers are confronted with the problem of searching a huge design space that has been shown to have widely varying performance and energy metrics for different accelerators, different application domains, and different use cases. To address this problem, numerous studies have evaluated specific applications across different accelerators. In this paper, we analyze an important domain of applications, referred to as sliding-window applications, when executing on FPGAs, GPUs, and multicores. For each device, we present optimization strategies and analyze use cases where each device is most effective. The results show that FPGAs can achieve speedup of up to 11x and 57x compared to GPUs and multicores, respectively, while also using orders of magnitude less energy.
Correntropy: Properties and Applications in Non-Gaussian Signal Processing
(2007)

The optimality of second-order statistics depends heavily on the assumption of Gaussianity. In this paper, we elucidate further the probabilistic and geometric meaning of the recently defined correntropy function as a localized similarity measure. A close relationship between correntropy and M-estimation is established. Connections and differences between correntropy and kernel methods are presented. As such correntropy has vastly different properties compared with second-order statistics that can be very useful in non-Gaussian signal processing, especially in the impulsive noise environment. Examples are presented to illustrate the technique.
Real-Time Optical Flow Calculations on FPGA and GPU Architectures: A Comparison Study
(2008)

FPGA devices have often found use as higher-performance alternatives to programmable processors for implementing a variety of computations. Applications successfully implemented on FPGAs have typically contained high levels of parallelism and have often used simple statically-scheduled control and modest arithmetic. Recently introduced computing devices such as coarse grain reconfigurable arrays, multi-core processors, and graphical processing units (GPUs) promise to significantly change the computational landscape for the implementation of high-speed real-time computing tasks. One reason for this is that these architectures take advantage of many of the same application characteristics that fit well on FPGAs. One real-time computing task, optical flow, is difficult to apply in robotic vision applications in practice because of its high computational and data rate requirements, and so is a good candidate for implementation on FPGAs and other custom computing architectures. In this paper, a tensor-based optical flow algorithm is implemented on both an FPGA and a GPU and the two implementations discussed. The two implementations had similar performance, but with the FPGA implementation requiring 12× more development time. Other comparison data for these two technologies is then given for three additional applications taken from a MIMO digital communication system design, providing additional examples of the relative capabilities of these two technologies.
Performance comparison of FPGA, GPU and CPU in image processing
(2009)

Many applications in image processing have high inherent parallelism. FPGAs have shown very high performance in spite of their low operational frequency by fully extracting the parallelism. In recent micro processors, it also becomes possible to utilize the parallelism using multi-cores which support improved SIMD instructions, though programmers have to use them explicitly to achieve high performance. Recent GPUs support a large number of cores, and have a potential for high performance in many applications. However, the cores are grouped, and data transfer between the groups is very limited. Programming tools for FPGA, SIMD instructions on CPU and a large number of cores on GPU have been developed, but it is still difficult to achieve high performance on these platforms. In this paper, we compare the performance of FPGA, GPU and CPU using three applications in image processing; two-dimensional filters, stereo-vision and k-means clustering, and make it clear which platform is faster under which conditions.
Scalable matrix inversion using MapReduce
(2014)

Matrix operations are a fundamental building block of many computational tasks in fields as diverse as scientific computing, machine learning, and data mining. Matrix inversion is an important matrix operation, but it is difficult to implement in today's popular parallel dataflow programming systems, such as MapReduce. The reason is that each element in the inverse of a matrix depends on multiple elements in the input matrix, so the computation is not easily partitionable. In this paper, we present a scalable and efficient technique for matrix inversion in MapReduce. Our technique relies on computing the LU decomposition of the input matrix and using that decomposition to compute the required matrix inverse. We present a technique for computing the LU decomposition and the matrix inverse using a pipeline of MapReduce jobs. We also present optimizations of this technique in the context of Hadoop. To the best of our knowledge, our technique is the first matrix inversion technique using MapReduce. We show experimentally that our technique has good scalability, enabling us to invert a 10^5 x 10^5 matrix in 5 hours on Amazon EC2. We also show that our technique outperforms ScaLAPACK, a state-of-the-art linear algebra package that uses MPI.
AMEE Guide No. 14: Outcome-based education: Part 1-An introduction to outcome-based education
(1999)

SUMM AR Y Outcome-based education, a performance-based approach at the cutting edge of curr iculum development, offers a powerful and appealing way of reforming and managing medical education. The emphasis is on the productÐ what sort of doctor will be producedÐ rather than on the educational process. In outcome-based education the educational outcomes are clearly and unambiguously speci ® ed. These determine the curr iculum content and its organisation, the teaching methods and strategies, the courses offered, the assessment process, the educational environment and the curriculum timetable.They also provide a framework for curr iculum evaluation. A doctor is a unique combination of different kinds of abilities. A three-circle model can be used to present the learning outcomes in medical education, with the tasks to be performed by the doctor in the inner core, the approaches to the performance of the tasks in the middle area, and the growth of the individual and his or her role in the practice of medicine in the outer area. Medical schools need to prepare young doctors to practise in an increasingly complex healthcare scene with changing patient and public expectations, and increasing demands from employing authorities. Outcome-based education offers many advantages as a way of achieving this. It emphasises relevance in the curriculum and accountability, and can provide a clear and unambiguous framework for curr iculum planning which has an intuitive appeal. It encourages the teacher and the student to share responsibility for learning and it can guide student assessment and course evaluation. What sort of outcomes should be covered in a curriculum, how should they be assessed and how should outcome-based education be implemented are issues that need to be addressed.
Comparative assessment of methods for aligning multiple genome sequences
(2010)

Multiple sequence alignment is a difficult computational problem. There have been compelling pleas for methods to assess whole-genome multiple sequence alignments and compare the alignments produced by different tools. We assess the four ENCODE alignments, each of which aligns 28 vertebrates on 554 Mbp of total input sequence. We measure the level of agreement among the alignments and compare their coverage and accuracy. We find a disturbing lack of agreement among the alignments not only in species distant from human, but even in mouse, a well-studied model organism. Overall, the assessment shows that Pecan produces the most accurate or nearly most accurate alignment in all species and genomic location categories, while still providing coverage comparable to or better than that of the other alignments in the placental mammals. Our assessment reveals that constructing accurate whole-genome multiple sequence alignments remains a significant challenge, particularly for noncoding regions and distantly related species.
Structured Feature Learning for Pose Estimation
(2016)

In this paper, we propose a structured feature learning framework to reason the correlations among body joints at the feature level in human pose estimation. Different from existing approaches of modeling structures on score maps or predicted labels, feature maps preserve substantially richer descriptions of body joints. The relationships between feature maps of joints are captured with the introduced geometrical transform kernels, which can be easily implemented with a convolution layer. Features and their relationships are jointly learned in an end-to-end learning system. A bi-directional tree structured model is proposed, so that the feature channels at a body joint can well receive information from other joints. The proposed framework improves feature learning substantially. With very simple post processing, it reaches the best mean PCP on the LSP and FLIC datasets. Compared with the baseline of learning features at each joint separately with ConvNet, the mean PCP has been improved by 18% on FLIC. The code is released to the public.
Power Electronic Transformer-Based Railway Traction Systems: Challenges and Opportunities
(2017)

In this paper, power electronic transformer (PET)-based railway traction systems are comprehensively reviewed according to the unique application features and requirements. By comparing PET and conventional line frequency transformer (LFT)-based systems, their pros and cons are summarized. By further reviewing all kinds of PET-based designs from the early concepts to the latest ones in the order of their publication dates, the developing trends are highlighted. By synthetically considering the requirements and the state of the art, the key challenges and opportunities are identified and discussed. It shows that although PET-based systems are still developing and far from mature, they are already superior to LFT-based systems in terms of system weight, efficiency, and functionalities especially for 15-kV/16.7-Hz applications. With the advancements on wide bandgap power devices, medium frequency transformers, and converters, PET systems will be even more promising and available for all types of railway tractions in the near future.
ACE: An Efficient Asynchronous Corner Tracker for Event Cameras
(2018)

The emergence of bio-inspired event cameras has opened up new exciting possibilities in high-frequency tracking, overcoming some of the limitations of traditional frame-based vision (e.g. motion blur during high-speed motions or saturation in scenes with high dynamic range). As a result, research has been focusing on the processing of their unusual output: an asynchronous stream of events. With the majority of existing techniques discretizing the event-stream into frame-like representations, we are yet to harness the true power of these cameras. In this paper, we propose the ACE tracker: a purely asynchronous framework to track corner-event features. Evaluation on benchmarking datasets reveals significant improvements in accuracy and computational efficiency in comparison to state-of-the-art event-based trackers. ACE achieves robust performance even in challenging scenarios, where traditional frame-based vision algorithms fail.